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Build and maintain big-data pipelines for financial-sector clients using Spark, Scala, and Python on Cloudera/Databricks.
Build scalable ETL pipelines and real-time data processing systems using Scala and Apache Spark, deploying on cloud platforms like Azure, AWS, or GCP.
Design and implement Azure-based streaming-to-batch data pipelines using Data Factory, Data Lake Storage, and PySpark/Scala in Python.
Build and maintain AI-driven data pipelines for financial crime detection at a fintech company using Spark, Python, and big-data tools.
Designs and implements scalable data pipelines using Scala, Apache Spark, and Databricks to process and integrate financial data in cloud environments.
Build and maintain large-scale data pipelines and cloud infrastructure using AWS, Spark/Scala, Python, and SQL to power analytics and ML workloads.
Senior Data Engineer builds and maintains cloud-based data pipelines and analytics infrastructure to enable data-driven decisions across Bunge’s global operations.
Senior Data Engineer building scalable big-data pipelines in AWS using Spark on Scala, optimizing performance for large datasets and collaborating with an international team.
Senior Data Engineer builds and maintains scalable data pipelines, cloud infrastructure, and ML models on Google Cloud using Python, SQL, dbt, and Databricks.
Build and maintain cloud-based data pipelines and models for marketing analytics, enabling 1:1 retargeting and CRM for global brands using Spark, Python, and GCP/AWS/Azure.
Build and maintain high-performance data pipelines for a real-time ad-tech platform, enabling ML models with clean, scalable data while working in a fast-paced engineering team.
Build and maintain cloud-based data pipelines and ETL processes to deliver clean, accessible datasets for enterprise clients in advertising and marketing technology.
Builds Azure-based data pipelines, lakehouse architectures, and Power BI reports using Data Factory, Databricks, and SQL.
Build and maintain scalable cloud data pipelines for a global travel platform, using AWS, Kafka, Spark, and Scala to process billions of daily events.
Build and maintain scalable data pipelines and lakehouses using Microsoft Fabric and Power BI, automating ingestion, transformation, and CI/CD workflows for analytics solutions.
Build and maintain scalable data pipelines and platforms using Spark, Scala, Kafka, and cloud tech to enable analytics and decision-making across BNP Paribas.
Build and maintain scalable data pipelines and cloud architectures to ingest, transform, and serve reliable data for analytics and reporting across hybrid environments.
Build and maintain scalable data pipelines using cloud platforms (AWS/Azure/GCP), Databricks, and tools like Spark and DBT to integrate and optimize data workflows for enterprise clients.
Designs and maintains scalable data pipelines, ETL/ELT processes, and cloud-based data platforms to support analytics and AI in high-security sectors like defense.
Build and maintain scalable data pipelines using cloud platforms (AWS/Azure/GCP), Databricks, and tools like Spark and DBT to integrate and transform data for clients.
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